Measuring Preferences using Conjoint Analytic Methods and Advanced Compositional Approaches

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Assoc. Prof. Martin Meissner (University of Southern Denmark/Department of Environmental and Business Economics)

Date: Thursday, 14/09/17 (09:30 – 18:00 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English


The participants of this course develop a sound understanding of the benefits of using conjoint analytic preferences measurement approaches and alternative advanced compositional approaches. Participants gain practical experience of using conjoint-analytic methods and developed a better understanding of the value of measuring preferences.

The course starts with introducing the basic concepts behind the measurement of stated preferences, specifically focusing on conjoint analysis. The most often used approaches, i.e. traditional conjoint analysis, adaptive conjoint analysis and choice-based conjoint analysis are introduced. We deliberate on advantages and disadvantages of the approaches and also discuss advanced compositional approaches, like pairwise-comparison based preference measurement and the adaptive self-explicated approach. During the workshop, we will further talk about all the important stages of designing a preference measurement study. We pay special attention to the types of research questions that conjoint analysis can answer. We also discuss the most important questions you should answer before setting up your preference measurement/conjoint study: What is the optimal choice of attributes and attribute level? What is a good experimental design? How should I design my survey design and present potential choice scenarios? How do I analyse the results?

Participants will have the opportunity to use Sawtooth Software on their own laptops and build their own conjoint analysis survey during the course. Based on this experience, participants will be able to improve the planning of their own future experiments.

Requirement of students: Basic knowledge in inferential statistics is recommended.

Recommended literature and pre-readings:

  • Bradlow, Eric T. (2005), “Current Issues and a ‘Wish List’ for Conjoint Analysis,” Applied Stochastic Models in Business and Industry, 21 (4-5), 319-323.
  • Hauser, John R. and Vithala Rao (2003), “Conjoint Analysis, Related Modeling, and Applications,” In Marketing Research and Modeling: Progress and Prospects, Wind, Jerry and Paul Green (eds.), New York: Springer, 141-168.

You have to register for the 11th International Research Workshop to participate in this course.